Analysis of culture and RNA isolation methods for precision-cut liver slices from cirrhotic rats.

Precision-cut liver slices (PCLS) are increasingly used as a model to investigate anti-fibrotic therapies. However, many studies use PCLS from healthy animals treated with pro-fibrotic stimuli in culture, which reflects only the early stages of fibrosis. The effects of different culture conditions on PCLS from cirrhotic animals has not been well characterized and there is no consensus on optimal methods. In this study, we report a method for the collection and culture of cirrhotic PCLS and compare the effect of common culture conditions on viability, function, and gene expression. Additionally, we compared three methods of RNA isolation and identified a protocol with high yield and purity. We observed significantly increased albumin production when cultured with insulin-transferrin-selenium and dexamethasone, and when incubated on a rocking platform. Culturing with insulin-transferrin-selenium and dexamethasone maintained gene expression closer to the levels in fresh slices. However, despite stable viability and function up to 4 days, we found significant changes in expression of key genes by day 2. Interestingly, we also observed that cirrhotic PCLS maintain viability in culture longer than slices from healthy animals. Due to the influence of matrix stiffness on fibrosis and hepatocellular function, it is important to evaluate prospective anti-fibrotic therapies in a platform that preserves tissue biomechanics. PCLS from cirrhotic animals represent a promising tool for the development of treatments for chronic liver disease.

Tradeoffs in the design of RNA thermometers.

The synthesis of RNA thermometers is aimed at achieving temperature responses with desired thresholds and sensitivities. Although previous works have generated thermometers with a variety of thresholds and sensitivities as well as guidelines for design, possible constraints in the achievable thresholds and sensitivities remain unclear. We addressed this issue using a two-state model and its variants, as well as melt profiles generated from thermodynamic computations. In the two-state model, we found that the threshold was inversely proportional to the sensitivity, in the case of a fixed energy difference between the two states. Notably, this constraint could persist in variations of the two-state model with sequentially unfolding states and branched parallel pathways. Furthermore, the melt profiles generated from a library of thermometers exhibited a similar constraint. These results should inform the design of RNA thermometers as well as other responses that are mediated in a similar fashion.

Atomistic insights into the reentrant phase-transitions in polyuracil and polylysine mixtures.

The phase separation of protein and RNA mixtures underpins the assembly and regulation of numerous membraneless organelles in cells. The ubiquity of protein-RNA condensates in cellular regulatory processes is in part due to their sensitivity to RNA concentration, which affects their physical properties and stability. Recent experiments with poly-cationic peptide-RNA mixtures have revealed closed-loop phase diagrams featuring lower and upper critical solution temperatures. These diagrams indicate reentrant phase transitions shaped by biomolecular interactions and entropic forces such as solvent and ion reorganization. We employed atomistic simulations to study mixtures with various RNA-polylysine stoichiometries and temperatures to elucidate the microscopic driving forces behind reentrant phase transitions in protein-RNA mixtures. Our findings reveal an intricate interplay between hydration, ion condensation, and specific RNA-polylysine hydrogen bonding, resulting in distinct stoichiometry-dependent phase equilibria governing stabilities and structures of the condensate phase. Our simulations show that reentrant transitions are accompanied by desolvation around the phosphate groups of RNA, with increased contacts between phosphate and lysine side chains. In RNA-rich systems at lower temperatures, RNA molecules can form an extensive pi-stacking and hydrogen bond network, leading to percolation. In protein-rich systems, no such percolation-induced transitions are observed. Furthermore, we assessed the performance of three prominent water force fields-Optimal Point Charge (OPC), TIP4P-2005, and TIP4P-D-in capturing reentrant phase transitions. OPC provided a superior balance of interactions, enabling effective capture of reentrant transitions and accurate characterization of changes in solvent reorganization. This study offers atomistic insights into the nature of reentrant phase transitions using simple model peptide and nucleotide mixtures. We believe that our results are broadly applicable to larger classes of peptide-RNA mixtures exhibiting reentrant phase transitions.

Mitochondrion-to-nucleus communication mediated by RNA export: a survey of potential mechanisms and players across eukaryotes.

The nucleus interacts with the other organelles to perform essential functions of the eukaryotic cell. Mitochondria have their own genome and communicate back to the nucleus in what is known as mitochondrial retrograde response. Information is transferred to the nucleus in many ways, leading to wide-ranging changes in nuclear gene expression and culminating with changes in metabolic, regulatory or stress-related pathways. RNAs are emerging molecules involved in this signalling. RNAs encode precise information and are involved in highly target-specific signalling, through a wide range of processes known as RNA interference. RNA-mediated mitochondrial retrograde response requires these molecules to exit the mitochondrion, a process that is still mostly unknown. We suggest that the proteins/complexes translocases of the inner membrane, polynucleotide phosphorylase, mitochondrial permeability transition pore, and the subunits of oxidative phosphorylation complexes may be responsible for RNA export.

Exploring functional conservation in silico: a new machine learning approach to RNA-editing.

Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed, with a remarkable impact in the increase of the complexity of the transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with an attention layer. These algorithms, combined with RNA-editing data coming from databases and variant calling from same-individual RNA and DNA-seq experiments from different species, allowed us to predict RNA-editing events using both primary sequence and secondary structure. Then, we devised a method for assessing conservation or divergence in the molecular mechanisms of editing completely in silico: the cross-testing analysis. This novel method not only helps to understand the conservation of the editing mechanism through evolution but could set the basis for achieving a better understanding of the adenosine-targeting mechanism in other fields.

[« ReNAissance ¼ of biotherapies with RNA]. / « ReNAissance ¼1 des biothérapies par ARN.

Many diseases originate from either the absence or defective expression of a given protein. For some of them, the lacking protein is secreted or can be taken up by cells when delivered exogenously. In such cases, therapies initially involved administering the physiological protein extracted from human tissues. Subsequently, genetic engineering enabled the production of proteins through cell fermentation after introducing the corresponding gene. For many other pathologies, the deficient protein cannot be delivered exogenously. Thus, an endogenous production of the therapeutic protein by the cells themselves is necessary. Messenger RNA (mRNA) technology, like its predecessor DNA, aims to supplement the genetic information needed to produce the therapeutic protein within the cells. However, unlike DNA-based therapies, mRNA transfer allows for transient expression of the protein of interest, which offers an advantage in numerous pathologies. Nonetheless, mastering the quantity, quality, and spatio-temporal regulation of protein production encoded by therapeutic mRNA remains a significant challenge for the development of this approach.

Title: « ReNAissance ¼1 des biothérapies par ARN. Abstract: Nombre de maladies ont pour origine une absence d'expression ou une expression défectueuse d'une protéine donnée. Pour certaines d'entre elles, la protéine faisant défaut est circulante et peut être captée par les cellules lorsqu'elle est délivrée de façon exogène. Dans ce cas, les thérapies ont d'abord consisté en l'administration de la protéine thérapeutique extraite de tissus humains. Par la suite, le génie génétique a permis la production des protéines par fermentation de cellules après y avoir introduit le gène correspondant. Pour beaucoup d'autres maladies, la protéine faisant défaut ne peut être délivrée de façon exogène. Une production endogène de la protéine thérapeutique, par les cellules elles-mêmes est donc nécessaire. La technologie de l'ARN messager (ARNm), comme celle la précédant de l'ADN, se propose de supplémenter, au cœur des cellules, l'information génétique nécessaire pour produire elles-mêmes la protéine thérapeutique. Cependant, contrairement aux thérapies utilisant l'ADN, le transfert d'ARNm permet une expression transitoire de la protéine d'intérêt ce qui constitue un avantage dans nombre de maladies. La maîtrise de la quantité, de la qualité et de la régulation spatio-temporelle de la production d'une protéine codée par l'ARNm thérapeutique représente, néanmoins, un défi important pour le développement de cette approche.

Human red blood cells express the RNA sensor TLR7.

Red blood cells (RBCs) express the nucleic acid-binding toll-like receptor 9 (TLR9) and bind CpG-containing DNA. However, whether human RBCs express other nucleic acid-binding TLRs is unknown. Here we show that human RBCs express the RNA sensor TLR7. TLR7 is present on the red cell membrane and is associated with the RBC membrane protein Band 3. In patients with SARS-CoV2-associated sepsis, TLR7-Band 3 interactions in the RBC membrane are increased when compared with healthy controls. In vitro, RBCs bind synthetic ssRNA and RNA from ssRNA viruses. Thus, RBCs may serve as a previously unrecognized sink for exogenous RNA, expanding the repertoire of non-gas exchanging functions performed by RBCs.

[Progress of research on circular RNA encoding proteins in disease].

With the advance of research, non-coding RNA has been found to surpass the traditional definition to directly code functional proteins by coding sequence elements and binding with ribosomes. Among the non-coding RNAs, the function of circRNA encoded proteins has been most extensively studied. This study has used "circRNA", "encoded", and "translation" as the key words to search the PubMed and Web of Science databases. The retrieved literature was screened and traced, with the translation mechanism, related research methods, and correlation with diseases of circRNA reviewed. CircRNA can translate proteins through a non-cap-dependent pathway. Multiple molecular techniques, in particular mass spectrometry analysis, have important value in identifying unique peptide segments of circRNA encoded proteins for confirming their existence. The proteins encoded by the circRNA are involved in the pathogenesis of diseases of the digestive, neurological, urinary systems and the breast, and have the potential to serve as novel targets for disease diagnosis and treatment. This article has provided a comprehensive review for the basic theory, experimental methods, and disease-related research in the field of circRNA translation, which may provide clues for the identification of new diagnostic and therapeutic targets.

[Advances in mapping analysis of ribonucleic acid modifications through sequencing].

Over 170 chemical modifications have been discovered in various types of ribonucleic acids (RNAs), including messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and small nuclear RNA (snRNA). These RNA modifications play crucial roles in a wide range of biological processes such as gene expression regulation, RNA stability maintenance, and protein translation. RNA modifications represent a new dimension of gene expression regulation known as the "epitranscriptome". The discovery of RNA modifications and the relevant writers, erasers, and readers provides an important basis for studies on the dynamic regulation and physiological functions of RNA modifications. Owing to the development of detection technologies for RNA modifications, studies on RNA epitranscriptomes have progressed to the single-base resolution, multilayer, and full-coverage stage. Transcriptome-wide methods help discover new RNA modification sites and are of great importance for elucidating the molecular regulatory mechanisms of epitranscriptomics, exploring the disease associations of RNA modifications, and understanding their clinical applications. The existing RNA modification sequencing technologies can be categorized according to the pretreatment approach and sequencing principle as direct high-throughput sequencing, antibody-enrichment sequencing, enzyme-assisted sequencing, chemical labeling-assisted sequencing, metabolic labeling sequencing, and nanopore sequencing technologies. These methods, as well as studies on the functions of RNA modifications, have greatly expanded our understanding of epitranscriptomics. In this review, we summarize the recent progress in RNA modification detection technologies, focusing on the basic principles, advantages, and limitations of different methods. Direct high-throughput sequencing methods do not require complex RNA pretreatment and allow for the mapping of RNA modifications using conventional RNA sequencing methods. However, only a few RNA modifications can be analyzed by high-throughput sequencing. Antibody enrichment followed by high-throughput sequencing has emerged as a crucial approach for mapping RNA modifications, significantly advancing the understanding of RNA modifications and their regulatory functions in different species. However, the resolution of antibody-enrichment sequencing is limited to approximately 100-200 bp. Although chemical crosslinking techniques can achieve single-base resolution, these methods are often complex, and the specificity of the antibodies used in these methods has raised concerns. In particular, the issue of off-target binding by the antibodies requires urgent attention. Enzyme-assisted sequencing has improved the accuracy of the localization analysis of RNA modifications and enables stoichiometric detection with single-base resolution. However, the enzymes used in this technique show poor reactivity, specificity, and sequence preference. Chemical labeling sequencing has become a widely used approach for profiling RNA modifications, particularly by altering reverse transcription (RT) signatures such as RT stops, misincorporations, and deletions. Chemical-assisted sequencing provides a sequence-independent RNA modification detection strategy that enables the localization of multiple RNA modifications. Additionally, when combined with the biotin-streptavidin affinity method, low-abundance RNA modifications can be enriched and detected. Nevertheless, the specificity of many chemical reactions remains problematic, and the development of specific reaction probes for particular modifications should continue in the future to achieve the precise localization of RNA modifications. As an indirect localization method, metabolic labeling sequencing specifically localizes the sites at which modifying enzymes act, which is of great significance in the study of RNA modification functions. However, this method is limited by the intracellular labeling of RNA and cannot be applied to biological samples such as clinical tissues and blood samples. Nanopore sequencing is a direct RNA-sequencing method that does not require RT or the polymerase chain reaction (PCR). However, challenges in analyzing the data obtained from nanopore sequencing, such as the high rate of false positives, must be resolved. Discussing sequencing analysis methods for various types of RNA modifications is instructive for the future development of novel RNA modification mapping technologies, and will aid studies on the functions of RNA modifications across the entire transcriptome.

A point cloud segmentation framework for image-based spatial transcriptomics.

Recent progress in image-based spatial RNA profiling enables to spatially resolve tens to hundreds of distinct RNA species with high spatial resolution. It presents new avenues for comprehending tissue organization. In this context, the ability to assign detected RNA transcripts to individual cells is crucial for downstream analyses, such as in-situ cell type calling. Yet, accurate cell segmentation can be challenging in tissue data, in particular in the absence of a high-quality membrane marker. To address this issue, we introduce ComSeg, a segmentation algorithm that operates directly on single RNA positions and that does not come with implicit or explicit priors on cell shape. ComSeg is applicable in complex tissues with arbitrary cell shapes. Through comprehensive evaluations on simulated and experimental datasets, we show that ComSeg outperforms existing state-of-the-art methods for in-situ single-cell RNA profiling and in-situ cell type calling. ComSeg is available as a documented and open source pip package at https://github.com/fish-quant/ComSeg .

ImmRNA: a database of RNAs associated with tumor immunity.

The relationship between different ribonucleic acids (RNAs) and tumor immunity has been widely investigated. However, a systematic description of tumor immune-related RNAs in different tumors is still lacking. We collected the relationship of tumor immune-related RNAs from the published literature and presented them in a user-friendly interface, "ImmRNA" (http://www.immrna.cn/), to provide a resource to study immune-RNA-cancer regulatory relations. The ImmRNA contains 49 996 curated entries. Each entry includes gene symbols, gene types, target genes, downstream effects, functions, immune cells, and other information. By rearranging and reanalyzing the data, our dataset contains the following key points: (i) providing the links between RNAs and the immune in cancers, (ii) displaying the downstream effects and functions of RNAs, (iii) listing immune cells and immune pathways related to RNA function, (iv) showing the relationship between RNAs and prognostic outcomes, and (v) exhibiting the experimental methods described in the article. ImmRNA provides a valuable resource for understanding the functions of tumor immune-related RNAs. Database URL:  http://www.immrna.cn/.

Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN.

The rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Most in silico tools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here, we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics simulations and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identifies all the experimentally resolved pockets and ranks them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field.

RNA 2'-O-methylation promotes persistent R-loop formation and AID-mediated IgH class switch recombination.

BACKGROUND: RNA-DNA hybrids or R-loops are associated with deleterious genomic instability and protective immunoglobulin class switch recombination (CSR). However, the underlying phenomenon regulating the two contrasting functions of R-loops is unknown. Notably, the underlying mechanism that protects R-loops from classic RNase H-mediated digestion thereby promoting persistence of CSR-associated R-loops during CSR remains elusive. RESULTS: Here, we report that during CSR, R-loops formed at the immunoglobulin heavy (IgH) chain are modified by ribose 2'-O-methylation (2'-OMe). Moreover, we find that 2'-O-methyltransferase fibrillarin (FBL) interacts with activation-induced cytidine deaminase (AID) associated snoRNA aSNORD1C to facilitate the 2'-OMe. Moreover, deleting AID C-terminal tail impairs its association with aSNORD1C and FBL. Disrupting FBL, AID or aSNORD1C expression severely impairs 2'-OMe, R-loop stability and CSR. Surprisingly, FBL, AID's interaction partner and aSNORD1C promoted AID targeting to the IgH locus. CONCLUSION: Taken together, our results suggest that 2'-OMe stabilizes IgH-associated R-loops to enable productive CSR. These results would shed light on AID-mediated CSR and explain the mechanism of R-loop-associated genomic instability.

If the 5' cap fits (wear it) - Non-canonical RNA capping.

RNA capping is a prominent RNA modification that influences RNA stability, metabolism, and function. While it was long limited to the study of the most abundant eukaryotic canonical m7G cap, the field recently went through a large paradigm shift with the discovery of non-canonical RNA capping in bacteria and ultimately all domains of life. The repertoire of non-canonical caps has expanded to encompass metabolite caps, including NAD, FAD, CoA, UDP-Glucose, and ADP-ribose, alongside alarmone dinucleoside polyphosphate caps, and methylated phosphate cap-like structures. This review offers an introduction into the field, presenting a summary of the current knowledge about non-canonical RNA caps. We highlight the often still enigmatic biological roles of the caps together with their processing enzymes, focusing on the most recent discoveries. Furthermore, we present the methods used for the detection and analysis of these non-canonical RNA caps and thus provide an introduction into this dynamic new field.

Lupus IgA1 autoantibodies synergize with IgG to enhance plasmacytoid dendritic cell responses to RNA-containing immune complexes.

Autoantibodies to nuclear antigens are hallmarks of systemic lupus erythematosus (SLE) where they contribute to pathogenesis. However, there remains a gap in our knowledge regarding how different isotypes of autoantibodies contribute to this autoimmune disease, including the production of the critical type I interferon (IFN) cytokines by plasmacytoid dendritic cells (pDCs) in response to immune complexes (ICs). We focused on IgA, which is the second-most prevalent isotype in serum and, along with IgG, is deposited in glomeruli in individuals with lupus nephritis. We show that individuals with SLE have serum IgA autoantibodies against most nuclear antigens, correlating with IgG against the same antigen. We investigated whether IgA autoantibodies against a major SLE autoantigen, Smith ribonucleoprotein (Sm/RNP), played a role in IC activation of pDCs. We found that pDCs expressed the IgA-specific Fc receptor, FcαR, and IgA1 autoantibodies synergized with IgG in RNA-containing ICs to generate robust primary blood pDC IFN-α responses in vitro. pDC responses to these ICs required both FcαR and FcγRIIa, showing synergy between these Fc receptors. Sm/RNP IC binding to and internalization by pDCs were greater when ICs contained both IgA1 and IgG. Circulating pDCs from individuals with SLE had higher binding of IgA1-containing ICs and higher expression of FcαR than pDCs from healthy control individuals. Although pDC FcαR expression correlated with the blood IFN-stimulated gene signature in SLE, Toll-like receptor 7 agonists, but not IFN-α, up-regulated pDC FcαR expression in vitro. Together, we show a mechanism by which IgA1 autoantibodies contribute to SLE pathogenesis.

Exploring the impact of primer length on efficient gene detection via high-throughput sequencing.

Reverse transcription (RT) is a crucial step in most RNA analysis methods. Optimizing protocols for this initial stage is critical for effective target detection, particularly when working with limited input RNA. Several factors, such as the input material quality and reaction conditions, influence RT efficiency. However, the effect of RT primer length on gene detection efficiency remains largely unknown. Thus, we investigate its impact by generating RNA-seq libraries with random RT primers of 6, 12, 18, or 24 nucleotides. To our surprise, the 18mer primer shows superior efficiency in overall transcript detection compared to the commonly used 6mer primer, especially in detecting longer RNA transcripts in complex human tissue samples. This study highlights the critical role of primer length in RT efficiency, which has significant potential to benefit various transcriptomic assays, from basic research to clinical diagnostics, given the central role of RT in RNA-related analyses.

Characterization of m6A Modifiers and RNA Modifications in Uterine Fibroids.

Uterine leiomyoma or fibroids are prevalent noncancerous tumors of the uterine muscle layer, yet their origin and development remain poorly understood. We analyzed RNA expression profiles of 15 epigenetic mediators in uterine fibroids compared to myometrium using publicly available RNA sequencing (RNA-seq) data. To validate our findings, we performed RT-qPCR on a separate cohort of uterine fibroids targeting these modifiers confirming our RNA-seq data. We then examined protein profiles of key N6-methyladenosine (m6A) modifiers in fibroids and their matched myometrium, showing no significant differences in concordance with our RNA expression profiles. To determine RNA modification abundance, mRNA and small RNA from fibroids and matched myometrium were analyzed by ultra-high performance liquid chromatography-mass spectrometry identifying prevalent m6A and 11 other known modifiers. However, no aberrant expression in fibroids was detected. We then mined a previously published dataset and identified differential expression of m6A modifiers that were specific to fibroid genetic subtype. Our analysis also identified m6A consensus motifs on genes previously identified to be dysregulated in uterine fibroids. Overall, using state-of-the-art mass spectrometry, RNA expression, and protein profiles, we characterized and identified differentially expressed m6A modifiers in relation to driver mutations. Despite the use of several different approaches, we identified limited differential expression of RNA modifiers and associated modifications in uterine fibroids. However, considering the highly heterogenous genomic and cellular nature of fibroids, and the possible contribution of single molecule m6A modifications to fibroid pathology, there is a need for greater in-depth characterization of m6A marks and modifiers in a larger and diverse patient cohort.

TracrRNA reprogramming enables direct PAM-independent detection of RNA with diverse DNA-targeting Cas12 nucleases.

Many CRISPR-Cas immune systems generate guide (g)RNAs using trans-activating CRISPR RNAs (tracrRNAs). Recent work revealed that Cas9 tracrRNAs could be reprogrammed to convert any RNA-of-interest into a gRNA, linking the RNA's presence to Cas9-mediated cleavage of double-stranded (ds)DNA. Here, we reprogram tracrRNAs from diverse Cas12 nucleases, linking the presence of an RNA-of-interest to dsDNA cleavage and subsequent collateral single-stranded DNA cleavage-all without the RNA necessarily encoding a protospacer-adjacent motif (PAM). After elucidating nuclease-specific design rules, we demonstrate PAM-independent RNA detection with Cas12b, Cas12e, and Cas12f nucleases. Furthermore, rationally truncating the dsDNA target boosts collateral cleavage activity, while the absence of a gRNA reduces background collateral activity and enhances sensitivity. Finally, we apply this platform to detect 16 S rRNA sequences from five different bacterial pathogens using a universal reprogrammed tracrRNA. These findings extend tracrRNA reprogramming to diverse dsDNA-targeting Cas12 nucleases, expanding the flexibility and versatility of CRISPR-based RNA detection.

Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

As vast histological archives are digitised, there is a pressing need to be able to associate specific tissue substructures and incident pathology to disease outcomes without arduous annotation. Here, we learn self-supervised representations using a Vision Transformer, trained on 1.7 M histology images across 23 healthy tissues in 838 donors from the Genotype Tissue Expression consortium (GTEx). Using these representations, we can automatically segment tissues into their constituent tissue substructures and pathology proportions across thousands of whole slide images, outperforming other self-supervised methods (43% increase in silhouette score). Additionally, we can detect and quantify histological pathologies present, such as arterial calcification (AUROC = 0.93) and identify missing calcification diagnoses. Finally, to link gene expression to tissue morphology, we introduce RNAPath, a set of models trained on 23 tissue types that can predict and spatially localise individual RNA expression levels directly from H&E histology (mean genes significantly regressed = 5156, FDR 1%). We validate RNAPath spatial predictions with matched ground truth immunohistochemistry for several well characterised control genes, recapitulating their known spatial specificity. Together, these results demonstrate how self-supervised machine learning when applied to vast histological archives allows researchers to answer questions about tissue pathology, its spatial organisation and the interplay between morphological tissue variability and gene expression.

Controllable self-cleaning FET self-assembled RNA-cleaving DNAzyme based DNA nanotree for culture-free Staphylococcus aureus detection.

Staphylococcus aureus (SA) poses a serious risk to human and animal health, necessitating a low-cost and high-performance analytical platform for point-of-care diagnostics. Cellulose paper-based field-effect transistors (FETs) with RNA-cleaving DNAzymes (RCDs) can fulfill the low-cost requirements, however, its high hydrophilicity and lipophilicity hinder biochemical modification and result in low sensitivity, poor mechanical stability and poor fouling performance. Herein, we proposed a controllable self-cleaning FET to simplify biochemical modification and improve mechanical stability and antifouling performance. Then, we constructed an RCD-based DNA nanotree to significantly enhance the sensitivity for SA detection. For controllable self-cleaning FET, 1 H,1 H,2 H,2 H-perfluorodecyltrimethoxysilane based-polymeric nanoparticles were synthesized to decorate cellulose paper and whole carbon nanofilm wires. O2 plasma was applied to regulate to reduce fluorocarbon chain density, and then control the hydrophobic-oleophobic property in sensitive areas. Because negatively charged DNA affected the sensitivity of semiconducting FETs, three Y-shaped branches with low-cost were designed and applied to synthesize an RCD-based DNA-Nanotree based on similar DNA-origami technology, which further improved the sensitivity. The trunk of DNA-Nanotree was composed of RCD, and the canopy was self-assembled using multiple Y-shaped branches. The controllable self-cleaning FET biosensor was applied for SA detection without cultivation, which had a wide linear range from 1 to 105 CFU/mL and could detect a low value of 1 CFU/mL.